干旱气象 ›› 2023, Vol. 41 ›› Issue (1): 152-163.DOI: 10.11755/j.issn.1006-7639(2023)-01-0152

• 技术报告 • 上一篇    下一篇

对流尺度集合预报对川渝地区降水的预报性能分析

叶茂(), 吴钲(), 高松, 陈良吕, 游婷   

  1. 重庆市气象科学研究所,重庆 401147
  • 收稿日期:2022-05-05 修回日期:2022-10-09 出版日期:2023-02-28 发布日期:2023-02-28
  • 通讯作者: 吴钲(1985—),男,博士,高级工程师,主要从事数值模拟和资料同化研究。E-mail:wukgdqghg@163.com
  • 作者简介:叶茂(1994—),女,硕士,工程师,主要从事数值模拟研究。E-mail:ymyemao@163.com
  • 基金资助:
    中国气象局创新发展专项(CXFZ2022P017);重庆市自然科学基金面上项目(cstc2021jcyj-msxm4335);重庆市气象部门青年基金项目(QNJJ-202207);重庆市气象部门智慧气象技术创新团队项目(ZHCXTD-202002)

Analysis on precipitation forecast performance of convective-scale ensemble system in Sichuan-Chongqing region

YE Mao(), WU Zheng(), GAO Song, CHEN Lianglü, YOU Ting   

  1. Chongqing Institute of Meteorological Sciences, Chongqing 401147, China
  • Received:2022-05-05 Revised:2022-10-09 Online:2023-02-28 Published:2023-02-28

摘要:

为深入认识对流尺度集合预报对川渝地区降水的预报性能,利用2020—2021年暖季(5—9月)川渝地区7 213个自动气象站逐日降水观测数据,综合评估对流尺度集合预报系统的控制预报(Control Forecast, CNTL)、集合平均(Ensemble Mean, MEAN)和概率匹配平均(Probability-matched Ensemble Mean, PM)对川渝地区降水的预报能力,并对比不同起报时次(08:00和20:00,北京时,下同)的预报差异。结果表明:(1)PM和MEAN的预报性能相对CNTL有所提高,MEAN对中雨和大雨量级降水预报具有指示意义,PM对大量级降水具有明显的预报优势。(2)模式预报的降水频率在小雨量级相比观测呈区域一致的正偏差,中雨及以上量级降水的预报正偏差集中在大巴山、华蓥山、武陵山脉等高海拔山区,预报负偏差主要位于四川盆地和丘陵区域,MEAN对小雨和中雨(大雨和暴雨)的预报正(负)偏差最明显。(3)08:00起报的36 h时效临界成功指数(Critical Success Index, CSI)和命中率(Probability of Detection, POD)整体高于20:00起报的48 h时效预报结果,但08:00起报的降水频率对高海拔山区的高估更明显。(4)PM和MEAN对四川盆地2021年9月4—7日强降水过程的降水落区预报优于CNTL,这是因为集合预报能够更好地把握天气系统的位置和形状特征。

关键词: 集合预报, 对流尺度, 降水评估, 川渝地区

Abstract:

In order to learn more about the performance of convective-scale ensemble forecast system for precipitation prediction in the Sichuan-Chongqing region, the control forecast (CNTL), the ensemble mean (MEAN) and the probability-matched ensemble mean (PM) of convective-scale ensemble prediction system are comprehensively analyzed based on daily precipitation data collected at 7 213 stations in the Sichuan-Chongqing region in warm season (from May to September) from 2020 to 2021, and differences between rainfall forecasts starting at 08:00 and 20:00 are compared. Results are as follows: (1) The forecast performance of PM and MEAN is better than that of CNTL. MEAN is skillful at forecasting moderate rain and heavy rain, and PM has obvious advantages for large rainfall. (2) Positive forecast deviations of light rainfall frequency are obvious in the whole research region, while for moderate rain and above, positive deviations are concentrated in high-altitude mountains such as the Daba Mountain, the Huaying Mountain and the Wuling Mountain, and negative deviations are mainly located in the Sichuan Basin and hilly areas. Positive (negative) deviations of light rain and moderate rain (heavy rain and rainstorm) predicted by MEAN are more obvious than those predicted by CNTL and PM. (3) The critical success index (CSI) and probability of detection (POD) scores with lead time of 36 h for the forecasts starting at 08:00 are higher than those with lead time of 48 h for the forecasts starting at 20:00, but the overestimation of rainfall frequency starting at 08:00 is more obvious in high-altitude mountains. (4) Compared with CNTL, PM and MEAN are better for the rainfall area of the heavy rain process from September 4 to 7, 2021 in the Sichuan Basin, which is related to the fact that ensemble forecast can better capture the position and morphology of the weather system.

Key words: ensemble prediction, convective-scale, precipitation verification, the Sichuan-Chongqing region

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